MATH-170. added SynchronizedDescriptiveStatistics class.

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@590564 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Brent Worden 2007-10-31 05:38:58 +00:00
parent 2e8332522e
commit 6afeedf161
4 changed files with 195 additions and 394 deletions

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@ -1,251 +1,39 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* contributor license agreements. See the NOTICE file distributed with this
* work for additional information regarding copyright ownership. The ASF
* licenses this file to You under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
* http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law
* or agreed to in writing, software distributed under the License is
* distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the specific language
* governing permissions and limitations under the License.
*/
package org.apache.commons.math.stat.descriptive;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;
import org.apache.commons.math.random.RandomData;
import org.apache.commons.math.random.RandomDataImpl;
/**
* Test cases for the {@link Univariate} class.
*
* @version $Revision$ $Date$
* @version $Revision$ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
* 2007) $
*/
public final class DescriptiveStatisticsImplTest extends TestCase {
private double one = 1;
private float two = 2;
private int three = 3;
private double mean = 2;
private double sumSq = 18;
private double sum = 8;
private double var = 0.666666666666666666667;
private double std = Math.sqrt(var);
private double n = 4;
private double min = 1;
private double max = 3;
private double tolerance = 10E-15;
public final class DescriptiveStatisticsImplTest extends DescriptiveStatisticsTest {
public DescriptiveStatisticsImplTest(String name) {
super(name);
}
public void setUp() {
}
public static Test suite() {
TestSuite suite = new TestSuite(DescriptiveStatisticsImplTest.class);
suite.setName("DescriptiveStatistics Tests");
suite.setName("DescriptiveStatisticsImpl Tests");
return suite;
}
/** test stats */
public void testStats() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
assertEquals("total count",0,u.getN(),tolerance);
u.addValue(one);
u.addValue(two);
u.addValue(two);
u.addValue(three);
assertEquals("N",n,u.getN(),tolerance);
assertEquals("sum",sum,u.getSum(),tolerance);
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
assertEquals("var",var,u.getVariance(),tolerance);
assertEquals("std",std,u.getStandardDeviation(),tolerance);
assertEquals("mean",mean,u.getMean(),tolerance);
assertEquals("min",min,u.getMin(),tolerance);
assertEquals("max",max,u.getMax(),tolerance);
u.clear();
assertEquals("total count",0,u.getN(),tolerance);
}
public void testN0andN1Conditions() throws Exception {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
assertTrue("Mean of n = 0 set should be NaN",
Double.isNaN( u.getMean() ) );
assertTrue("Standard Deviation of n = 0 set should be NaN",
Double.isNaN( u.getStandardDeviation() ) );
assertTrue("Variance of n = 0 set should be NaN",
Double.isNaN(u.getVariance() ) );
u.addValue(one);
assertTrue( "Mean of n = 1 set should be value of single item n1",
u.getMean() == one);
assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
assertTrue( "Variance of n = 1 set should be zero",
u.getVariance() == 0);
protected DescriptiveStatistics createDescriptiveStatistics() {
return new DescriptiveStatisticsImpl();
}
public void testSkewAndKurtosis() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
double[] testArray =
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
for( int i = 0; i < testArray.length; i++) {
u.addValue( testArray[i]);
}
assertEquals("mean", 12.40455, u.getMean(), 0.0001);
assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
}
public void testProductAndGeometricMean() throws Exception {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
u.setWindowSize(10);
u.addValue( 1.0 );
u.addValue( 2.0 );
u.addValue( 3.0 );
u.addValue( 4.0 );
//assertEquals( "Product not expected",
// 24.0, u.getProduct(), Double.MIN_VALUE );
assertEquals( "Geometric mean not expected",
2.213364, u.getGeometricMean(), 0.00001 );
// Now test rolling - StorelessDescriptiveStatistics should discount the contribution
// of a discarded element
for( int i = 0; i < 10; i++ ) {
u.addValue( i + 2 );
}
// Values should be (2,3,4,5,6,7,8,9,10,11)
//assertEquals( "Product not expected", 39916800.0,
// u.getProduct(), 0.00001 );
assertEquals( "Geometric mean not expected", 5.755931,
u.getGeometricMean(), 0.00001 );
}
public void testGetSortedValues() {
double[] test1 = {5,4,3,2,1};
double[] test2 = {5,2,1,3,4,0};
double[] test3 = {1};
int[] testi = null;
double[] test4 = null;
RandomData rd = new RandomDataImpl();
tstGetSortedValues(test1);
tstGetSortedValues(test2);
tstGetSortedValues(test3);
for (int i = 0; i < 10; i++) {
testi = rd.nextPermutation(10,6);
test4 = new double[6];
for (int j = 0; j < testi.length; j++) {
test4[j] = (double) testi[j];
}
tstGetSortedValues(test4);
}
for (int i = 0; i < 10; i++) {
testi = rd.nextPermutation(10,5);
test4 = new double[5];
for (int j = 0; j < testi.length; j++) {
test4[j] = (double) testi[j];
}
tstGetSortedValues(test4);
}
}
private void tstGetSortedValues(double[] test) {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
for (int i = 0; i < test.length; i++) {
u.addValue(test[i]);
}
double[] sorted = u.getSortedValues();
if (sorted.length != test.length) {
fail("wrong length for sorted values array");
}
for (int i = 0; i < sorted.length-1; i++) {
if (sorted[i] > sorted[i+1]) {
fail("sorted values out of sequence");
}
}
}
public void testPercentiles() {
double[] test = {5,4,3,2,1};
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
for (int i = 0; i < test.length; i++) {
u.addValue(test[i]);
}
assertEquals("expecting min",1,u.getPercentile(5),10E-12);
assertEquals("expecting max",5,u.getPercentile(99),10E-12);
assertEquals("expecting middle",3,u.getPercentile(50),10E-12);
try {
u.getPercentile(0);
fail("expecting IllegalArgumentException for getPercentile(0)");
} catch (IllegalArgumentException ex) {
;
}
try {
u.getPercentile(120);
fail("expecting IllegalArgumentException for getPercentile(120)");
} catch (IllegalArgumentException ex) {
;
}
u.clear();
double[] test2 = {1,2,3,4};
for (int i = 0; i < test2.length; i++) {
u.addValue(test2[i]);
}
assertEquals("Q1",1.25,u.getPercentile(25),10E-12);
assertEquals("Q3",3.75,u.getPercentile(75),10E-12);
assertEquals("Q2",2.5,u.getPercentile(50),10E-12);
u.clear();
double[] test3 = {1};
for (int i = 0; i < test3.length; i++) {
u.addValue(test3[i]);
}
assertEquals("Q1",1,u.getPercentile(25),10E-12);
assertEquals("Q3",1,u.getPercentile(75),10E-12);
assertEquals("Q2",1,u.getPercentile(50),10E-12);
u.clear();
RandomData rd = new RandomDataImpl();
int[] testi = rd.nextPermutation(100,100); // will contain 0-99
for (int j = 0; j < testi.length; j++) {
u.addValue((double) testi[j]); //OK, laugh at me for the cast
}
for (int i = 1; i < 100; i++) {
assertEquals("percentile " + i,
(double) i-1 + (double) i*(.01), u.getPercentile(i),10E-12);
}
u.clear();
double[] test4 = {1,2,3,4,100};
for (int i = 0; i < test4.length; i++) {
u.addValue(test4[i]);
}
assertEquals("80th",80.8,u.getPercentile(80),10E-12);
u.clear();
assertTrue("empty value set should return NaN",
Double.isNaN(u.getPercentile(50)));
}
}

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@ -29,122 +29,40 @@ import org.apache.commons.math.random.RandomDataImpl;
*
* @version $Revision$ $Date$
*/
public final class DescriptiveStatisticsTest extends TestCase {
private double one = 1;
private float two = 2;
private int three = 3;
private double mean = 2;
private double sumSq = 18;
private double sum = 8;
public abstract class DescriptiveStatisticsTest extends TestCase {
private double var = 0.666666666666666666667;
private double std = Math.sqrt(var);
private double n = 4;
private double min = 1;
private double max = 3;
private double mean = 2;
private double min = 1;
private double n = 4;
private double one = 1;
private double std = Math.sqrt(var);
private double sum = 8;
private double sumSq = 18;
private int three = 3;
private double tolerance = 10E-15;
private float two = 2;
public DescriptiveStatisticsTest(String name) {
super(name);
}
public void setUp() {
}
public static Test suite() {
TestSuite suite = new TestSuite(DescriptiveStatisticsTest.class);
suite.setName("Descriptive Statistics Tests");
return suite;
}
/** test stats */
public void testStats() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
assertEquals("total count",0,u.getN(),tolerance);
u.addValue(one);
u.addValue(two);
u.addValue(two);
u.addValue(three);
assertEquals("N",n,u.getN(),tolerance);
assertEquals("sum",sum,u.getSum(),tolerance);
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
assertEquals("var",var,u.getVariance(),tolerance);
assertEquals("std",std,u.getStandardDeviation(),tolerance);
assertEquals("mean",mean,u.getMean(),tolerance);
assertEquals("min",min,u.getMin(),tolerance);
assertEquals("max",max,u.getMax(),tolerance);
u.clear();
assertEquals("total count",0,u.getN(),tolerance);
}
protected abstract DescriptiveStatistics createDescriptiveStatistics();
public void testN0andN1Conditions() throws Exception {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
assertTrue("Mean of n = 0 set should be NaN",
Double.isNaN( u.getMean() ) );
assertTrue("Standard Deviation of n = 0 set should be NaN",
Double.isNaN( u.getStandardDeviation() ) );
assertTrue("Variance of n = 0 set should be NaN",
Double.isNaN(u.getVariance() ) );
u.addValue(one);
assertTrue( "Mean of n = 1 set should be value of single item n1",
u.getMean() == one);
assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
assertTrue( "Variance of n = 1 set should be zero",
u.getVariance() == 0);
}
public void testSkewAndKurtosis() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
double[] testArray =
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
for( int i = 0; i < testArray.length; i++) {
u.addValue( testArray[i]);
}
assertEquals("mean", 12.40455, u.getMean(), 0.0001);
assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
public void setUp() {
}
public void testProductAndGeometricMean() throws Exception {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
u.setWindowSize(10);
u.addValue( 1.0 );
u.addValue( 2.0 );
u.addValue( 3.0 );
u.addValue( 4.0 );
//assertEquals( "Product not expected",
// 24.0, u.getProduct(), Double.MIN_VALUE );
assertEquals( "Geometric mean not expected",
2.213364, u.getGeometricMean(), 0.00001 );
// Now test rolling - StorelessDescriptiveStatistics should discount the contribution
// of a discarded element
for( int i = 0; i < 10; i++ ) {
u.addValue( i + 2 );
}
// Values should be (2,3,4,5,6,7,8,9,10,11)
//assertEquals( "Product not expected", 39916800.0,
// u.getProduct(), 0.00001 );
assertEquals( "Geometric mean not expected", 5.755931,
u.getGeometricMean(), 0.00001 );
}
public void testAddValue() {
double[] test1 = {5,4,3,2,1,0};
double[] test2 = {5,2,1,0,4,3};
DescriptiveStatistics stats = DescriptiveStatistics.newInstance();
DescriptiveStatistics stats = createDescriptiveStatistics();
stats.setWindowSize(12);
for(int i = 0; i < test1.length; i++){
@ -189,7 +107,7 @@ public final class DescriptiveStatisticsTest extends TestCase {
//System.out.println(test3[i] + " "+test2[i-6]);
}
}
}
public void testGetSortedValues() {
double[] test1 = {5,4,3,2,1};
@ -219,28 +137,54 @@ public final class DescriptiveStatisticsTest extends TestCase {
}
}
private void tstGetSortedValues(double[] test) {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
u.setWindowSize(test.length);
for (int i = 0; i < test.length; i++) {
u.addValue(test[i]);
public void testN0andN1Conditions() throws Exception {
DescriptiveStatistics u = createDescriptiveStatistics();
assertTrue("Mean of n = 0 set should be NaN",
Double.isNaN( u.getMean() ) );
assertTrue("Standard Deviation of n = 0 set should be NaN",
Double.isNaN( u.getStandardDeviation() ) );
assertTrue("Variance of n = 0 set should be NaN",
Double.isNaN(u.getVariance() ) );
u.addValue(one);
assertTrue( "Mean of n = 1 set should be value of single item n1",
u.getMean() == one);
assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
assertTrue( "Variance of n = 1 set should be zero",
u.getVariance() == 0);
}
public void testNewInstanceClassNull() {
try {
DescriptiveStatistics.newInstance((Class)null);
fail("null is not a valid descriptive statistics class");
} catch (NullPointerException ex) {
// success
} catch (Exception ex) {
fail();
}
double[] sorted = u.getSortedValues();
if (sorted.length != test.length) {
fail("wrong length for sorted values array");
}
for (int i = 0; i < sorted.length-1; i++) {
if (sorted[i] > sorted[i+1]) {
fail("sorted values out of sequence");
}
}
public void testNewInstanceClassValid() {
try {
DescriptiveStatistics u = DescriptiveStatistics.newInstance(
DescriptiveStatisticsImpl.class);
assertNotNull(u);
assertTrue(u instanceof DescriptiveStatisticsImpl);
} catch (InstantiationException ex) {
fail();
} catch (IllegalAccessException ex) {
fail();
}
}
public void testPercentiles() {
double[] test = {5,4,3,2,1};
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
DescriptiveStatistics u = createDescriptiveStatistics();
u.setWindowSize(110);
for (int i = 0; i < test.length; i++) {
u.addValue(test[i]);
@ -301,10 +245,39 @@ public final class DescriptiveStatisticsTest extends TestCase {
assertTrue("empty value set should return NaN",
Double.isNaN(u.getPercentile(50)));
}
public void testProductAndGeometricMean() throws Exception {
DescriptiveStatistics u = createDescriptiveStatistics();
u.setWindowSize(10);
u.addValue( 1.0 );
u.addValue( 2.0 );
u.addValue( 3.0 );
u.addValue( 4.0 );
//assertEquals( "Product not expected",
// 24.0, u.getProduct(), Double.MIN_VALUE );
assertEquals( "Geometric mean not expected",
2.213364, u.getGeometricMean(), 0.00001 );
// Now test rolling - StorelessDescriptiveStatistics should discount the contribution
// of a discarded element
for( int i = 0; i < 10; i++ ) {
u.addValue( i + 2 );
}
// Values should be (2,3,4,5,6,7,8,9,10,11)
//assertEquals( "Product not expected", 39916800.0,
// u.getProduct(), 0.00001 );
assertEquals( "Geometric mean not expected", 5.755931,
u.getGeometricMean(), 0.00001 );
}
/** test stats */
public void testSerialization() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
DescriptiveStatistics u = createDescriptiveStatistics();
assertEquals("total count",0,u.getN(),tolerance);
u.addValue(one);
u.addValue(two);
@ -325,51 +298,60 @@ public final class DescriptiveStatisticsTest extends TestCase {
u2.clear();
assertEquals("total count",0,u2.getN(),tolerance);
}
public void testSkewAndKurtosis() {
DescriptiveStatistics u = createDescriptiveStatistics();
double[] testArray =
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
for( int i = 0; i < testArray.length; i++) {
u.addValue( testArray[i]);
}
assertEquals("mean", 12.40455, u.getMean(), 0.0001);
assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
}
public void testNewInstanceClassNull() {
try {
DescriptiveStatistics.newInstance((Class)null);
fail("null is not a valid descriptive statistics class");
} catch (NullPointerException ex) {
// success
} catch (Exception ex) {
fail();
}
/** test stats */
public void testStats() {
DescriptiveStatistics u = createDescriptiveStatistics();
assertEquals("total count",0,u.getN(),tolerance);
u.addValue(one);
u.addValue(two);
u.addValue(two);
u.addValue(three);
assertEquals("N",n,u.getN(),tolerance);
assertEquals("sum",sum,u.getSum(),tolerance);
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
assertEquals("var",var,u.getVariance(),tolerance);
assertEquals("std",std,u.getStandardDeviation(),tolerance);
assertEquals("mean",mean,u.getMean(),tolerance);
assertEquals("min",min,u.getMin(),tolerance);
assertEquals("max",max,u.getMax(),tolerance);
u.clear();
assertEquals("total count",0,u.getN(),tolerance);
}
public void testNewInstanceClassValid() {
try {
DescriptiveStatistics u = DescriptiveStatistics.newInstance(
DescriptiveStatisticsImpl.class);
assertNotNull(u);
assertTrue(u instanceof DescriptiveStatisticsImpl);
} catch (InstantiationException ex) {
fail();
} catch (IllegalAccessException ex) {
fail();
}
}
public void testWindowSize() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
u.setWindowSize(1234);
assertEquals(1234, u.getWindowSize());
u.addValue(1.0);
u.addValue(2.0);
u.addValue(3.0);
u.addValue(4.0);
u.addValue(5.0);
assertEquals(5, u.getN());
u.setWindowSize(DescriptiveStatistics.INFINITE_WINDOW);
assertEquals(5, u.getN());
public void testToString() {
DescriptiveStatistics u = createDescriptiveStatistics();
assertTrue(u.toString().indexOf("NaN") > 0);
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
double[] testArray =
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
for( int i = 0; i < testArray.length; i++) {
u.addValue( testArray[i]);
}
assertTrue(u.toString().indexOf("NaN") == -1);
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
}
public void testWindowing() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
DescriptiveStatistics u = createDescriptiveStatistics();
u.setWindowSize(2);
u.addValue(1.0);
@ -385,18 +367,37 @@ public final class DescriptiveStatisticsTest extends TestCase {
assertEquals(3.0, u.getMean(), tolerance);
}
public void testToString() {
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
assertTrue(u.toString().indexOf("NaN") > 0);
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
double[] testArray =
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
for( int i = 0; i < testArray.length; i++) {
u.addValue( testArray[i]);
}
assertTrue(u.toString().indexOf("NaN") == -1);
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
public void testWindowSize() {
DescriptiveStatistics u = createDescriptiveStatistics();
u.setWindowSize(1234);
assertEquals(1234, u.getWindowSize());
u.addValue(1.0);
u.addValue(2.0);
u.addValue(3.0);
u.addValue(4.0);
u.addValue(5.0);
assertEquals(5, u.getN());
u.setWindowSize(DescriptiveStatistics.INFINITE_WINDOW);
assertEquals(5, u.getN());
}
private void tstGetSortedValues(double[] test) {
DescriptiveStatistics u = createDescriptiveStatistics();
u.setWindowSize(test.length);
for (int i = 0; i < test.length; i++) {
u.addValue(test[i]);
}
double[] sorted = u.getSortedValues();
if (sorted.length != test.length) {
fail("wrong length for sorted values array");
}
for (int i = 0; i < sorted.length-1; i++) {
if (sorted[i] > sorted[i+1]) {
fail("sorted values out of sequence");
}
}
}
}

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@ -95,6 +95,9 @@ Commons Math Release Notes</title>
MaxIterationsExceededException and return 0 or 1, resp. if the argument
is more than 20 standard deviations from the mean.
</action>
<action dev="brentworden" type="update" issue="MATH-170" due-to="David J. M. Karlsen">
Added SynchronizedDescriptiveStatistics class.
</action>
</release>
<release version="1.1" date="2005-12-17"
description="This is a maintenance release containing bug fixes and enhancements.

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@ -199,7 +199,16 @@ while (line != null) {
}
in.close();
</source>
</dd>
</dd>
<dt>Compute statistics in a thread-safe manner</dt>
<br/>
<dd>Use a <code>ThreadSafeDescriptiveStatistics</code> instance
<source>
// Create a SynchronizedDescriptiveStatistics instance and
// use as any other DescriptiveStatistics instance
DescriptiveStatistics stats = DescriptiveStatistics.newInstance(SynchronizedDescriptiveStatistics.class);
</source>
</dd>
</dl>
</p>
</subsection>